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Natural Language Processing with TensorFlow

You're reading from   Natural Language Processing with TensorFlow Teach language to machines using Python's deep learning library

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Product type Paperback
Published in May 2018
Publisher Packt
ISBN-13 9781788478311
Length 472 pages
Edition 1st Edition
Languages
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Authors (2):
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Thushan Ganegedara Thushan Ganegedara
Author Profile Icon Thushan Ganegedara
Thushan Ganegedara
Motaz Saad Motaz Saad
Author Profile Icon Motaz Saad
Motaz Saad
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Toc

Table of Contents (14) Chapters Close

Preface 1. Introduction to Natural Language Processing FREE CHAPTER 2. Understanding TensorFlow 3. Word2vec – Learning Word Embeddings 4. Advanced Word2vec 5. Sentence Classification with Convolutional Neural Networks 6. Recurrent Neural Networks 7. Long Short-Term Memory Networks 8. Applications of LSTM – Generating Text 9. Applications of LSTM – Image Caption Generation 10. Sequence-to-Sequence Learning – Neural Machine Translation 11. Current Trends and the Future of Natural Language Processing A. Mathematical Foundations and Advanced TensorFlow Index

Comparing skip-gram with CBOW


Before looking at the performance differences and investigating reasons, let's remind ourselves about the fundamental difference between the skip-gram and CBOW methods.

As shown in the following figures, given a context and a target word, skip-gram observes only the target word and a single word of the context in a single input/output tuple. However, CBOW observes the target word and all the words in the context in a single sample. For example, if we assume the phrase dog barked at the mailman, skip-gram sees an input-output tuple such as ["dog", "at"] at a single time step, whereas CBOW sees an input-output tuple [["dog","barked","the","mailman"], "at"]. Therefore, in a given batch of data, CBOW receives more information than skip-gram about the context of a given word. Let's next see how this difference affects the performance of the two algorithms.

As shown in the preceding figures, the CBOW model has access to more information (inputs) at a given time compared...

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